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## Ultralytics YOLOv8 Example Applications
This repository features a collection of real-world applications and walkthroughs, provided as either Python files or notebooks. Explore the examples below to see how YOLOv8 can be integrated into various applications.
### Ultralytics YOLO Example Applications
| Title | Format | Contributor |
| -------------------------------------------------------------------------------------------------------------- | ------------------ | --------------------------------------------------- |
| [YOLO ONNX Detection Inference with C++](./YOLOv8-CPP-Inference) | C++/ONNX | [Justas Bartnykas](https://github.com/JustasBart) |
| [YOLO OpenCV ONNX Detection Python](./YOLOv8-OpenCV-ONNX-Python) | OpenCV/Python/ONNX | [Farid Inawan](https://github.com/frdteknikelektro) |
| [YOLO .Net ONNX Detection C#](https://www.nuget.org/packages/Yolov8.Net) | C# .Net | [Samuel Stainback](https://github.com/sstainba) |
| [YOLOv8 on NVIDIA Jetson(TensorRT and DeepStream)](https://wiki.seeedstudio.com/YOLOv8-DeepStream-TRT-Jetson/) | Python | [Lakshantha](https://github.com/lakshanthad) |
### How to Contribute
We welcome contributions from the community in the form of examples, applications, and guides. To contribute, please follow these steps:
1. Create a pull request (PR) with the `[Example]` prefix in the title, adding your project folder to the `examples/` directory in the repository.
1. Ensure that your project meets the following criteria:
- Utilizes the `ultralytics` package.
- Includes a `README.md` file with instructions on how to run the project.
- Avoids adding large assets or dependencies unless absolutely necessary.
- The contributor is expected to provide support for issues related to their examples.
If you have any questions or concerns about these requirements, please submit a PR, and we will be more than happy to guide you.